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Working Patterns Report
This report seeks to classify employees by their daily collaboration habits. We use Email and Teams Instant Message (IM) data to measure employee activity during each hour of the day, and group employees that share similar habits in 6 core archetypes. The method complements our traditional workweek span and after-hours analysis, by providing a more detailed view of activity throughout the day.
Among other things, this report should allow analysts to answer:
How many employees are concentrating their collaboration within the expecting working schedule (e.g. 9-5)?
How many employees are working on a more flexible schedule, going beyond 9-5 but taking breaks?
How many employees are working beyond the regular working schedule? How are those hours distributed?
How many employees appear to be struggling to disconnect / are always-on?
Data Overview
The data used is a Hourly Collaboration Query.
There are 150 employees in this dataset.
Date ranges from 2019-10-06 to 2019-12-01.
There are 5 (estimated) HR attributes in the data:
PersonId, Domain, IsInternal, IsActive, Organization
There are 147 active employees out of all in the dataset.
Variable name check:
No collaboration hour metric exists in the data.
No instant message hour metric exists in the data.
Common Patterns
Archetypes
Split by HR Attribute
Time Dynamics
0 < 3 hours on
1 Standard with breaks workday
2 Standard continuous workday
3 Standard flexible workday
4 Long flexible workday
5 Long continuous workday
6 Always on (13h+)
